Transcript
Hi, I'm Rohit Agarwal. Welcome to our series on building the AI control plane. Today we're talking about why enterprises need an AI control plane. Think about how we all first used generative AI. It was simple. You open an AI app, you asked a question, and you got a response. Request in, answer out. And when AI was mostly answering questions, the focus was prompts, responses, and productivity. But today, the enterprise ecosystem looks completely different. AI has evolved from simply generating responses to agents that can execute code and take autonomous actions. Teams are connecting models to business data, connecting tools and business data, MCP servers, and even enterprise systems to their AI agents. AI is no longer something employees use. It's becoming part of how work gets done. With this shift, AI in the enterprise has turned into a chaotic web. We have enterprise agents, MCP servers, endpoints, all of your different users talking to SaaS tools, coding agents, LLMs, all interacting with each other. This creates an incredibly noisy and unmanaged complex traffic pattern. This web isn't even your whole company. It's just the footprint of a single team inside your enterprise today. Multiply this across dozens of departments, hundreds of developers, think engineering, finance, HR, and so much more. It quickly becomes completely unmanageable, leaving enterprise leaders facing three massive questions. Can you see all your AI activity? Can you control all of these token costs? And can you secure every AI interaction? These are the true barriers to AI adoption today. And at scale, traditional security tools cannot help secure your AI innovation. Firewalls, endpoint agents, and manual code reviews were designed for static applications, not thousands of autonomous agents moving data at machine speed. If you rely on old methods, your defenses break the second a developer connects a new model to your enterprise data. Goldman Sachs claims that by 2030, consumer and enterprise agents will drive usage to around 120 quadrillion tokens per month. At that scale, organizations need to place controls over AI because what they manage today is the smallest it'll ever be. The chaos of the AI enterprise typically creates a false trade-off, innovate or stay safe. But you don't have to make that choice. The solution is to build an AI control plane. Every interaction flows through this control plane, creating a centralized view of all the AI activity within your enterprise. The centralized AI gateway does three things. Discover all the AI usage within your enterprise to see how and what AI is being used across the enterprise and track token consumption and cost. Govern all your AI interactions to really just help secure and control model and tool access while preventing data leakage, prompt injection, and unsafe outputs in real time. And finally, secure every agent that we've been talking about so that you can enforce identity-aware controls for agents and their actions. So, why trust Prisma Airs? Because it's the most comprehensive platform, securing the entire AI lifecycle end-to-end. Our AI gateway unifies governance, runtime protection, and access controls into a single platform. It's trusted by the world's most demanding organizations, processing more than 2 trillion tokens per day with five nines of uptime and sub-millisecond latency. I'm proud to say that today, Prisma Airs AI gateway is generally available to all users. In the next video, we'll cover how the AI gateway discovers AI usage in your organization and the benefits you get with complete visibility. Stay tuned.
